A hybrid intelligent system for distributed dynamic scheduling

This chapter addresses the resolution of dynamic scheduling by means of meta-heuristic and multi-agent systems. Scheduling is an important aspect of automation in manufacturing systems. Several contributions have been proposed, but the problem is far from being solved satisfactorily, especially if scheduling concerns real world applications. The proposed multi-agent scheduling system assumes the existence of several resource agents (which are decision-making entities based on meta-heuristics) distributed inside the manufacturing system that interact with other agents in order to obtain optimal or near-optimal global performances.

Determination of polyphenols in wines by reaction with 4-aminoantipyrine and photometric flow-injection analysis

A new flow-injection analytical procedure is proposed for the determination of the total amount of polyphenols in wines; the method is based on the formation of a colored complex between 4-aminoantipyrine and phenols, in the presence of an oxidizing reagent. The oxidizing agents hexacyanoferrate(III), peroxodisulfate, and tetroxoiodate(VII) were tested. Batch trials were first performed to select appropriate oxidizing agents, pH, and concentration ratios of reagents, on the basis of their effect on the stability of the colored complex. Conditions selected as a result of these trials were implemented in a flow-injection analytical system in which the influence of injection volume, flow rate, and reaction- coil length, was evaluated. Under the optimum conditions the total amount of polyphenols, expressed as gallic acid, could be determined within a concentration range of 36 to 544 mg L–1, and with a sensitivity of 344 L mol–1 cm–1 and an RSD <1.1%. The reproducibility of analytical readings was indicative of standard deviations <2%. Interference from sugars, tartaric acid, ascorbic acid, methanol, ammonium sulfate, and potassium chloride was negligible. The proposed system was applied to the determination of total polyphenols in red wines, and enabled analysis of approximately 55 samples h–1. Results were usually precise and accurate; the RSD was <3.9% and relative errors, by the Folin–Ciocalteu method, <5.1%.